Processing and interpretation of real-time data from downhole and surface sensors

• US 20040010374A1
• Filed: 05/20/2003
• Published: 01/15/2004
• Est. Priority Date: 05/21/2002
• Status: Active Grant

• Current Assignee: Schlumberger Technology Corporation (SLB)
• Original Assignee: Schlumberger Technology Corporation (SLB)
• Inventors: Navarro, Jose, Ramakrishnan, Terizhandur S., Raghuraman, Bhavani, Stephenson, Kenneth E., Venkataramanan, Lalitha
• Granted Patent: US 8,612,193 B2
• Time in Patent Office: Days
• US Class Current: 702/13
• CPC Class Codes: E21B 43/00 Methods or apparatus for obtaining oil, gas, water, soluble or meltable materials or a slurry of minerals from wells applicable only to water E03B
• CPC Class Codes: E21B 47/00 Survey of boreholes or wells monitoring pressure or flow of drilling fluid E21B21/08

Abstract

In accordance with an embodiment of the present invention, a method of processing large volumes of data to allow for real-time reservoir management is disclosed, comprising: a) acquiring a first data series from a first reservoir sensor; b) establishing a set of criteria based on reservoir management objectives, sensor characteristics, sensor location, nature of the reservoir, and data storage optimization, etc.; c) identifying one or more subsets of the first data series meeting at least one of the criteria; and optionally d) generating one or more second data series based on at least one of the subsets. This methodology may be repeated for numerous reservoir sensors. This methodology allows for intelligent evaluation of sensor data by using carefully established criteria to intelligently select one or more subsets of data. In an alternative embodiment, sensor data from one or more sensors may be evaluated while processing data from a different sensor.

Claims

1. A method of processing large volumes of data to allow for real-time reservoir management, comprising:

a) acquiring a first data series from a first reservoir sensor;

b) establishing a set of criteria based on at least one of the group consisting of reservoir management objectives, sensor characteristics, sensor location, nature of the reservoir, and data storage optimization; and

c) identifying one or more subsets of said first data series meeting at least one of said criteria.

2. The method of claim 1, further comprising:

d) generating one or more second data series based on at least one of said one or more subsets.

3. The method of claim 2, further comprising repeating (a), (b), (c) and (d) for one or more additional reservoir sensors.

4. The method of claim 2, wherein said one or more second data series are further based on one or more of said set of criteria.

5. The method of claim 3, further comprising stamping first data series from said first and additional reservoir sensors using one or more common parameters.

6. The method of claim 3, further comprising commonly compressing first data series from said first and additional reservoir sensors.

7. The method of claim 1, wherein said first data series is collected at a first acquisition rate.

8. The method of claim 7, wherein said first acquisition rate is temporarily increased upon the identification of one or more data points meeting at least one of said set of criteria.

9. The method of claim 1, further comprising adjusting said set of criteria.

10. The method of claim 1, wherein said set of criteria includes establishing relevant time scales.

11. The method of claim 1, wherein said set of criteria includes establishing a binning width.

12. The method of claim 10, wherein said binning width is based on the signal to noise ratio of at least one of said one or more reservoir sensors.

13. The method of claim 1, wherein said set of criteria includes establishing a decimation interval.

14. The method of claim 2, wherein acquiring said first data series includes storing said first data series.

15. The method of claim 14, wherein storing includes uploading said data from a local unit to a remote server.

16. The method of claim 15, wherein said first data series is stored in time-stamped compressed batch files.

17. The method of claim 16, further comprising displaying at least one of said one or more second data series on a remote computer or portable electronic device.

18. The method of claim 2, further comprising interpreting at least one of said one or more second data series.

19. The method of claim 18, wherein interpreting at least one of said one or more second data series includes analyzing changes in the reservoir characteristics or reservoir hardware.

20. The method of claim 18, wherein interpreting at least one of said one or more second data series includes tracking parameters derived from at least one of said one or more second data series.

21. The method of claim 20, further comprising modeling at least one of said one or more second data series.

22. The method of claim 21, wherein modeling includes running one or more forward models to simulate at least one of said one or more second data series.

23. The method of claim 21, wherein modeling includes running an inversion algorithm using at least one of said one or more second data series.

24. The method of claim 21, further comprising performing a regression analysis.

25. The method of claim 24, wherein said regression analysis includes a history match using substantially all of said first data series.

26. A method of processing large volumes of data to allow for real-time reservoir management, comprising:

a) acquiring a first data series from a first reservoir sensor;

b) establishing a set of criteria based on at least one of the group consisting of reservoir management objectives, sensor characteristics, sensor location, nature of the reservoir, and data storage optimization;

c) examining said first data series to identify one or more regions of interest based on at least one of said set of criteria;

d) accessing said acquired first data series corresponding to said one or more regions of interest; and

e) generating one or more second data series based on said accessed first data series.

27. The method of claim 26, further comprising repeating (a), (b), (c), (d), and (e) for one or more additional reservoir sensors.

28. The method of claim 26, wherein (d) further includes generating one or more subsets of said first series data corresponding to said one or more regions of interest, and wherein (e) further includes generating said one or more second data series based on said one or more subsets.

29. The method of claim 26, wherein (c) includes identifying the start and stop points of at least one of said one or more regions of interest.

30. The method of claim 26, wherein acquiring said first data series includes storing said first data series.

31. The method of claim 30, wherein storing includes uploading said data from a local unit to a remote server.

32. The method of claim 31, wherein said first data series is stored in time-stamped compressed batch files.

33. A method of processing large volumes of data to allow for real-time reservoir management, comprising:

a) acquiring a plurality of first data series from a plurality of reservoir sensors;

b) establishing a set of criteria;

c) identifying one or more subsets of said plurality of first data series meeting at least one of said set of criteria; and

d) generating a plurality of second data series based on at least one of said one or more subsets.

34. The method of claim 33, wherein at least one of said plurality of second data series is based on at least one subset identified from a different first data series.

35. The method of claim 33, further comprising adjusting said set of criteria.

36. The method of claim 33, wherein said set of criteria is based on at least one of the group consisting of reservoir management objectives, sensor characteristics, sensor location, nature of the reservoir, and data storage optimization.

37. The method of claim 33, further comprising time-stamping first data series from said first and additional reservoir sensors.

38. The method of claim 33, further comprising commonly compressing first data series from said first and additional reservoir sensors.

39. The method of claim 33, further comprising adjusting said set of criteria.

40. The method of claim 33, wherein said set of criteria includes establishing a relevant time scales.

41. The method of claim 33, wherein said set of criteria includes establishing a binning width.

42. The method of claim 41, wherein said binning width is based on the signal to noise ratio of at least one of said one or more reservoir sensors.

43. The method of claim 33, wherein said set of criteria includes establishing a decimation interval.

44. The method of claim 33, wherein acquiring said first data series includes storing said first data series.

45. The method of claim 44, wherein storing includes uploading said data from a local unit to a remote server.

46. The method of claim 45, wherein said first data series is stored in time-stamped compressed batch files.

47. The method of claim 33, further comprising displaying at least one of said plurality of second data series on a remote computer or portable electronic device.

48. The method of claim 33, further comprising interpreting at least one of said plurality of second data series.

49. The method of claim 48, wherein interpreting at least one of said plurality of second data series includes analyzing changes in the reservoir characteristics or reservoir hardware.

50. The method of claim 48, wherein interpreting at least one of said plurality of second data series includes tracking parameters derived from at least one of said plurality of second data series.

51. The method of claim 50, further comprising modeling at least one of said plurality of second data series.

52. The method of claim 51, wherein modeling includes running one or more forward models to simulate at least one of said plurality of second data series.

53. The method of claim 51, wherein modeling includes running an inversion algorithm using at least one of said plurality of second data series.

54. The method of claim 51, further comprising performing a regression analysis.

55. The method of claim 54, wherein said regression analysis includes a history match using substantially all of at least one of said plurality of first data series.